1.pace中采用的vgg16模型与之前使用的vgg16模型相差较多,无法进行对比
没有能够复现出paper中一模一样的结果,pace也存在随机性,但结果相差不大
2.目前的效果
m1:在class内进行聚类
m2:对整个testing context进行聚类
m3:昨天新提出的方法
| model精度 | 聚类个数 | 50 | 60 | 70 | 80 | 90 | 100 | 110 | 120 | 130 | 140 | 150 | 160 | 170 | 180 | |||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| mnist | PACE(paper) | 98.68% | 0.603 | 0.319 | 0.088 | 0.070 | 0.245 | 0.320 | 0.419 | 0.487 | 0.551 | 0.611 | 0.653 | 0.703 | 0.732 | 0.764 | ||
| PACE(recur) | 98.68% | 0.641 | 0.347 | 0.109 | 0.054 | 0.233 | 0.310 | 0.411 | 0.480 | 0.545 | 0.606 | 0.649 | 0.695 | 0.728 | 0.761 | |||
| PACE(recur) | 98.72% | 1.280 | 1.280 | 1.280 | 1.280 | 1.280 | 1.280 | 1.280 | 1.280 | 0.517 | 0.566 | 0.613 | 0.659 | 0.688 | 0.721 | |||
| SRS | 98.68% | 1.303 | 1.537 | 1.374 | 1.183 | 1.274 | 1.209 | 1.077 | 1.025 | 1.193 | 1.014 | 0.942 | 0.974 | 0.855 | 0.836 | |||
| SRS | 98.72% | 1.745 | 1.367 | 1.330 | 1.578 | 1.335 | 1.106 | 1.272 | 0.768 | 0.944 | 1.043 | 0.845 | 0.779 | 0.783 | 1.023 | |||
| m2 | 98.72% | 20 | 0.681 | 0.359 | 0.071 | 0.030 | 0.156 | 0.270 | 0.354 | 0.373 | 0.258 | 0.159 | 0.053 | 0.030 | 0.090 | 0.169 | ||
| 12 | 1.280 | 0.333 | 0.149 | 0.060 | 0.144 | 0.249 | 0.363 | 0.440 | 0.511 | 0.566 | 0.613 | 0.022 | 0.495 | 0.377 | ||||
| m3(1396) | 98.72% | 20 | 1.280 | 1.280 | 0.149 | 0.019 | 0.144 | 0.720 | 0.538 | 0.387 | 0.258 | 0.833 | 0.707 | 0.572 | 0.464 | 0.287 | ||
| m3(1396)_scale | 98.72% | 20 | 1.280 | 1.280 | 0.149 | 0.002 | 0.144 | 0.761 | 0.555 | 0.387 | 0.247 | 0.833 | 0.707 | 0.595 | 0.474 | 0.387 | ||
| m3(4000) | 98.72% | 20 | 0.761 | 0.415 | 1.661 | 1.220 | 0.894 | 0.720 | 0.555 | 0.359 | 0.258 | 0.848 | 0.707 | 1.204 | 1.073 | 0.955 | ||
| m3(4000)_scale | 98.72% | 20 | 1.280 | 1.280 | 0.169 | 0.014 | 0.169 | 0.290 | 0.371 | 0.447 | 0.511 | 0.138 | 0.045 | 0.583 | 0.485 | 0.918 | ||
| vgg16 | PACE(recur) | 87.41% | 2.786 | 2.754 | 4.139 | 2.590 | 2.590 | 2.590 | 2.498 | 2.673 | 2.666 | 3.304 | 3.923 | 3.785 | 2.531 | 1.976 | ||
| SRS | 87.41% | 4.737 | 4.103 | 4.637 | 3.947 | 3.671 | 3.620 | 3.034 | 3.116 | 3.122 | 2.869 | 2.490 | 2.370 | 2.356 | 2.692 | |||
| m2 | 87.41% | 15 | 3.096 | 2.410 | 1.299 | 0.231 | 0.230 | 0.709 | 0.878 | 0.090 | 0.282 | 0.176 | 0.077 | 0.011 | 0.237 | 0.858 | ||
| m3(1224) | 87.41% | 15 | 1.410 | 2.410 | 0.453 | 3.660 | 2.795 | 2.944 | 2.725 | 2.410 | 1.914 | 0.981 | 1.884 | 2.410 | 2.030 | 1.299 | ||
| m2(1224)_scale | 87.41% | 15 | 1.696 | 0.743 | 0.453 | 0.090 | 1.601 | 0.155 | 0.137 | 0.923 | 0.187 | 0.360 | 0.509 | 0.453 | 0.275 | 0.299 | ||
| m3(4000) | 87.41% | 15 | 3.737 | 4.359 | 4.311 | 3.866 | 3.140 | 4.410 | 5.428 | 5.592 | 4.204 | 3.839 | 3.410 | 2.410 | 2.030 | 1.854 | ||
| m3(4000)_scale | 87.41% | 15 | 0.345 | 0.726 | 0.086 | 1.334 | 0.368 | 1.479 | 0.137 | 0.633 | 0.487 | 0.267 | 0.590 | 1.340 | 1.414 | 1.354 |
